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kfda  

Kernel Fisher Discriminant Analysis
View on CRAN: Click here


Download and install kfda package within the R console
Install from CRAN:
install.packages("kfda")

Install from Github:
library("remotes")
install_github("cran/kfda")

Install by package version:
library("remotes")
install_version("kfda", "1.0.0")



Attach the package and use:
library("kfda")
Maintained by
Donghwan Kim
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-09-27
Latest Update: 2017-09-27
Description:
Kernel Fisher Discriminant Analysis (KFDA) is performed using Kernel Principal Component Analysis (KPCA) and Fisher Discriminant Analysis (FDA). There are some similar packages. First, 'lfda' is a package that performs Local Fisher Discriminant Analysis (LFDA) and performs other functions. In particular, 'lfda' seems to be impossible to test because it needs the label information of the data in the function argument. Also, the 'ks' package has a limited dimension, which makes it difficult to analyze properly. This package is a simple and practical package for KFDA based on the paper of Yang, J., Jin, Z., Yang, J. Y., Zhang, D., and Frangi, A. F. (2004) .
How to cite:
Donghwan Kim (2017). kfda: Kernel Fisher Discriminant Analysis. R package version 1.0.0, https://cran.r-project.org/web/packages/kfda. Accessed 25 Jun. 2026.
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Complete documentation for kfda
Functions, R codes and Examples using the kfda R package
Some associated functions: kfda . kfda.predict . 
Some associated R codes: kfda.R . kfda.predict.R .  Full kfda package functions and examples
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